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Proceedings Paper

Optimal structure sampling for etch model calibration
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Paper Abstract

Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels as well as the choice of calibration patterns is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels designed to capture the finest details of the resist contours and represent precisely any etch bias. By evaluating the etch kernels on various structures it is possible to map their etch signatures in a multi-dimensional space and analyze them to find an optimal sampling of structures to train an etch model. The method was specifically applied to a contact layer containing many different geometries and was used to successfully select appropriate calibration structures. The proposed kernels evaluated on these structures were combined to train an etch model significantly better than the standard one.

Paper Details

Date Published: 24 March 2017
PDF: 11 pages
Proc. SPIE 10147, Optical Microlithography XXX, 101470I (24 March 2017); doi: 10.1117/12.2257994
Show Author Affiliations
François Weisbuch, GLOBALFOUNDRIES Dresden (Germany)
Andrey Lutich, GLOBALFOUNDRIES Dresden (Germany)
Jirka Schatz, GLOBALFOUNDRIES Dresden (Germany)

Published in SPIE Proceedings Vol. 10147:
Optical Microlithography XXX
Andreas Erdmann; Jongwook Kye, Editor(s)

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